Overview

Brought to you by YData

Dataset statistics

Number of variables40
Number of observations2599
Missing cells29372
Missing cells (%)28.3%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory4.3 MiB
Average record size in memory1.7 KiB

Variable types

Text15
Categorical15
Numeric4
Unsupported6

Alerts

cvo_type has constant value " "Constant
cme_reqhours has constant value "0"Constant
isWFV has constant value "1"Constant
isCredStrm has constant value "1"Constant
Needs_Search_Info has constant value "0"Constant
CertificationBody is highly overall correlated with isManual and 4 other fieldsHigh correlation
autoemail is highly overall correlated with autofax and 2 other fieldsHigh correlation
autofax is highly overall correlated with autoemail and 2 other fieldsHigh correlation
isManual is highly overall correlated with CertificationBodyHigh correlation
isValidate is highly overall correlated with CertificationBodyHigh correlation
latitude is highly overall correlated with obsoleteHigh correlation
link is highly overall correlated with autoemail and 2 other fieldsHigh correlation
longitude is highly overall correlated with obsoleteHigh correlation
obsolete is highly overall correlated with CertificationBody and 2 other fieldsHigh correlation
payfee is highly overall correlated with CertificationBodyHigh correlation
ver_elec is highly overall correlated with CertificationBody and 3 other fieldsHigh correlation
nation is highly imbalanced (72.7%)Imbalance
inactive is highly imbalanced (85.4%)Imbalance
obsolete is highly imbalanced (99.5%)Imbalance
isManual is highly imbalanced (73.3%)Imbalance
addr has 237 (9.1%) missing valuesMissing
homehtml has 1059 (40.7%) missing valuesMissing
latitude has 2375 (91.4%) missing valuesMissing
longitude has 2375 (91.4%) missing valuesMissing
extension has 2595 (99.8%) missing valuesMissing
note has 2588 (99.6%) missing valuesMissing
username has 2599 (100.0%) missing valuesMissing
password has 2599 (100.0%) missing valuesMissing
LegacyCD has 2599 (100.0%) missing valuesMissing
lastvalidated has 2599 (100.0%) missing valuesMissing
validatedby has 2599 (100.0%) missing valuesMissing
CertificationBody has 2543 (97.8%) missing valuesMissing
Search_Info_Text has 2599 (100.0%) missing valuesMissing
cd has unique valuesUnique
link has unique valuesUnique
username is an unsupported type, check if it needs cleaning or further analysisUnsupported
password is an unsupported type, check if it needs cleaning or further analysisUnsupported
LegacyCD is an unsupported type, check if it needs cleaning or further analysisUnsupported
lastvalidated is an unsupported type, check if it needs cleaning or further analysisUnsupported
validatedby is an unsupported type, check if it needs cleaning or further analysisUnsupported
Search_Info_Text is an unsupported type, check if it needs cleaning or further analysisUnsupported
payfee has 2369 (91.2%) zerosZeros
latitude has 111 (4.3%) zerosZeros
longitude has 111 (4.3%) zerosZeros

Reproduction

Analysis started2024-09-19 13:48:18.582066
Analysis finished2024-09-19 13:48:26.677461
Duration8.1 seconds
Software versionydata-profiling vv4.10.0
Download configurationconfig.json

Variables

cd
Text

UNIQUE 

Distinct2599
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size149.9 KiB
2024-09-19T19:18:27.253671image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Length

Max length10
Median length10
Mean length9.9976914
Min length4

Characters and Unicode

Total characters25984
Distinct characters46
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2599 ?
Unique (%)100.0%

Sample

1st row9318
2nd rowAAAASF
3rd rowAAAHC
4th rowAAAP
5th rowAABIM
ValueCountFrequency (%)
9318 1
 
< 0.1%
aapsfp 1
 
< 0.1%
aamft432 1
 
< 0.1%
aacp 1
 
< 0.1%
aaahc 1
 
< 0.1%
aaap 1
 
< 0.1%
aabim 1
 
< 0.1%
aabip 1
 
< 0.1%
aabma 1
 
< 0.1%
aacadd 1
 
< 0.1%
Other values (2589) 2589
99.6%
2024-09-19T19:18:28.406965image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
12981
50.0%
A 1767
 
6.8%
C 997
 
3.8%
P 993
 
3.8%
S 928
 
3.6%
M 857
 
3.3%
N 816
 
3.1%
D 812
 
3.1%
O 766
 
2.9%
B 714
 
2.7%
Other values (36) 4353
 
16.8%

Most occurring categories

ValueCountFrequency (%)
Space Separator 12981
50.0%
Uppercase Letter 12691
48.8%
Decimal Number 149
 
0.6%
Lowercase Letter 100
 
0.4%
Other Punctuation 63
 
0.2%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
A 1767
13.9%
C 997
 
7.9%
P 993
 
7.8%
S 928
 
7.3%
M 857
 
6.8%
N 816
 
6.4%
D 812
 
6.4%
O 766
 
6.0%
B 714
 
5.6%
T 558
 
4.4%
Other values (16) 3483
27.4%
Lowercase Letter
ValueCountFrequency (%)
v 83
83.0%
o 6
 
6.0%
c 3
 
3.0%
a 2
 
2.0%
r 1
 
1.0%
l 1
 
1.0%
h 1
 
1.0%
n 1
 
1.0%
d 1
 
1.0%
m 1
 
1.0%
Decimal Number
ValueCountFrequency (%)
3 54
36.2%
4 47
31.5%
2 39
26.2%
1 3
 
2.0%
9 2
 
1.3%
8 2
 
1.3%
0 1
 
0.7%
5 1
 
0.7%
Space Separator
ValueCountFrequency (%)
12981
100.0%
Other Punctuation
ValueCountFrequency (%)
/ 63
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 13193
50.8%
Latin 12791
49.2%

Most frequent character per script

Latin
ValueCountFrequency (%)
A 1767
13.8%
C 997
 
7.8%
P 993
 
7.8%
S 928
 
7.3%
M 857
 
6.7%
N 816
 
6.4%
D 812
 
6.3%
O 766
 
6.0%
B 714
 
5.6%
T 558
 
4.4%
Other values (26) 3583
28.0%
Common
ValueCountFrequency (%)
12981
98.4%
/ 63
 
0.5%
3 54
 
0.4%
4 47
 
0.4%
2 39
 
0.3%
1 3
 
< 0.1%
9 2
 
< 0.1%
8 2
 
< 0.1%
0 1
 
< 0.1%
5 1
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 25984
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
12981
50.0%
A 1767
 
6.8%
C 997
 
3.8%
P 993
 
3.8%
S 928
 
3.6%
M 857
 
3.3%
N 816
 
3.1%
D 812
 
3.1%
O 766
 
2.9%
B 714
 
2.7%
Other values (36) 4353
 
16.8%

txt
Text

Distinct2555
Distinct (%)98.5%
Missing6
Missing (%)0.2%
Memory size884.1 KiB
2024-09-19T19:18:28.857837image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Length

Max length300
Median length300
Mean length300
Min length300

Characters and Unicode

Total characters777900
Distinct characters65
Distinct categories8 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2518 ?
Unique (%)97.1%

Sample

1st rowVA New Jersey Health Care System-East Orange
2nd rowAmerican Association for Accreditation of Ambulatory Surgery Facilities
3rd rowAccreditation Association Ambulatory Health Care
4th rowAmerican Academy of Addiction Psychiatry
5th rowAmerican Audiology Board of Intraoperative Monitoring
ValueCountFrequency (%)
of 1873
 
13.3%
board 1404
 
10.0%
american 623
 
4.4%
390
 
2.8%
state 318
 
2.3%
department 267
 
1.9%
medical 196
 
1.4%
examiners 186
 
1.3%
health 185
 
1.3%
medicine 183
 
1.3%
Other values (1520) 8430
60.0%
2024-09-19T19:18:30.268391image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
678233
87.2%
a 9506
 
1.2%
o 8916
 
1.1%
i 8813
 
1.1%
e 8533
 
1.1%
r 7010
 
0.9%
t 6206
 
0.8%
n 6025
 
0.8%
s 4865
 
0.6%
c 4488
 
0.6%
Other values (55) 35305
 
4.5%

Most occurring categories

ValueCountFrequency (%)
Space Separator 678233
87.2%
Lowercase Letter 85870
 
11.0%
Uppercase Letter 12558
 
1.6%
Other Punctuation 807
 
0.1%
Dash Punctuation 414
 
0.1%
Open Punctuation 6
 
< 0.1%
Close Punctuation 6
 
< 0.1%
Decimal Number 6
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a 9506
11.1%
o 8916
10.4%
i 8813
10.3%
e 8533
9.9%
r 7010
 
8.2%
t 6206
 
7.2%
n 6025
 
7.0%
s 4865
 
5.7%
c 4488
 
5.2%
l 3345
 
3.9%
Other values (16) 18163
21.2%
Uppercase Letter
ValueCountFrequency (%)
B 1557
12.4%
A 1516
12.1%
C 1131
9.0%
P 1083
 
8.6%
S 1020
 
8.1%
M 1018
 
8.1%
D 715
 
5.7%
N 709
 
5.6%
O 584
 
4.7%
H 455
 
3.6%
Other values (16) 2770
22.1%
Other Punctuation
ValueCountFrequency (%)
& 386
47.8%
/ 287
35.6%
. 71
 
8.8%
, 59
 
7.3%
' 3
 
0.4%
! 1
 
0.1%
Decimal Number
ValueCountFrequency (%)
8 2
33.3%
0 2
33.3%
5 2
33.3%
Space Separator
ValueCountFrequency (%)
678233
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 414
100.0%
Open Punctuation
ValueCountFrequency (%)
( 6
100.0%
Close Punctuation
ValueCountFrequency (%)
) 6
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 679472
87.3%
Latin 98428
 
12.7%

Most frequent character per script

Latin
ValueCountFrequency (%)
a 9506
 
9.7%
o 8916
 
9.1%
i 8813
 
9.0%
e 8533
 
8.7%
r 7010
 
7.1%
t 6206
 
6.3%
n 6025
 
6.1%
s 4865
 
4.9%
c 4488
 
4.6%
l 3345
 
3.4%
Other values (42) 30721
31.2%
Common
ValueCountFrequency (%)
678233
99.8%
- 414
 
0.1%
& 386
 
0.1%
/ 287
 
< 0.1%
. 71
 
< 0.1%
, 59
 
< 0.1%
( 6
 
< 0.1%
) 6
 
< 0.1%
' 3
 
< 0.1%
8 2
 
< 0.1%
Other values (3) 5
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 777900
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
678233
87.2%
a 9506
 
1.2%
o 8916
 
1.1%
i 8813
 
1.1%
e 8533
 
1.1%
r 7010
 
0.9%
t 6206
 
0.8%
n 6025
 
0.8%
s 4865
 
0.6%
c 4488
 
0.6%
Other values (55) 35305
 
4.5%

addr
Text

MISSING 

Distinct1364
Distinct (%)57.7%
Missing237
Missing (%)9.1%
Memory size207.6 KiB
2024-09-19T19:18:30.846453image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Length

Max length150
Median length42
Mean length37.636325
Min length7

Characters and Unicode

Total characters88897
Distinct characters72
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1072 ?
Unique (%)45.4%

Sample

1st row385 Tremont Ave
2nd rowPo Box 9500
3rd row5250 Old Orchard Rd
4th row400 Massasoit Ave
5th row563 Carter Ct
ValueCountFrequency (%)
st 673
 
7.4%
box 394
 
4.3%
po 393
 
4.3%
ave 338
 
3.7%
ste 270
 
3.0%
e 230
 
2.5%
rd 196
 
2.1%
w 196
 
2.1%
dr 189
 
2.1%
n 147
 
1.6%
Other values (1744) 6105
66.9%
2024-09-19T19:18:32.301935image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
55430
62.4%
e 2092
 
2.4%
0 2033
 
2.3%
t 1909
 
2.1%
1 1766
 
2.0%
o 1488
 
1.7%
a 1465
 
1.6%
S 1419
 
1.6%
r 1215
 
1.4%
n 1165
 
1.3%
Other values (62) 18915
 
21.3%

Most occurring categories

ValueCountFrequency (%)
Space Separator 55431
62.4%
Lowercase Letter 17039
 
19.2%
Decimal Number 9578
 
10.8%
Uppercase Letter 6763
 
7.6%
Other Punctuation 70
 
0.1%
Dash Punctuation 16
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 2092
12.3%
t 1909
11.2%
o 1488
 
8.7%
a 1465
 
8.6%
r 1215
 
7.1%
n 1165
 
6.8%
i 1142
 
6.7%
l 1051
 
6.2%
d 758
 
4.4%
s 718
 
4.2%
Other values (16) 4036
23.7%
Uppercase Letter
ValueCountFrequency (%)
S 1419
21.0%
B 698
10.3%
P 636
9.4%
W 486
 
7.2%
O 441
 
6.5%
C 429
 
6.3%
A 425
 
6.3%
R 325
 
4.8%
E 301
 
4.5%
N 285
 
4.2%
Other values (16) 1318
19.5%
Decimal Number
ValueCountFrequency (%)
0 2033
21.2%
1 1766
18.4%
2 1082
11.3%
5 971
10.1%
3 834
8.7%
4 791
 
8.3%
6 577
 
6.0%
8 523
 
5.5%
9 514
 
5.4%
7 487
 
5.1%
Other Punctuation
ValueCountFrequency (%)
, 23
32.9%
# 20
28.6%
. 19
27.1%
& 2
 
2.9%
: 2
 
2.9%
' 2
 
2.9%
/ 2
 
2.9%
Space Separator
ValueCountFrequency (%)
55430
> 99.9%
  1
 
< 0.1%
Dash Punctuation
ValueCountFrequency (%)
- 16
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 65095
73.2%
Latin 23802
 
26.8%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 2092
 
8.8%
t 1909
 
8.0%
o 1488
 
6.3%
a 1465
 
6.2%
S 1419
 
6.0%
r 1215
 
5.1%
n 1165
 
4.9%
i 1142
 
4.8%
l 1051
 
4.4%
d 758
 
3.2%
Other values (42) 10098
42.4%
Common
ValueCountFrequency (%)
55430
85.2%
0 2033
 
3.1%
1 1766
 
2.7%
2 1082
 
1.7%
5 971
 
1.5%
3 834
 
1.3%
4 791
 
1.2%
6 577
 
0.9%
8 523
 
0.8%
9 514
 
0.8%
Other values (10) 574
 
0.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 88895
> 99.9%
None 2
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
55430
62.4%
e 2092
 
2.4%
0 2033
 
2.3%
t 1909
 
2.1%
1 1766
 
2.0%
o 1488
 
1.7%
a 1465
 
1.6%
S 1419
 
1.6%
r 1215
 
1.4%
n 1165
 
1.3%
Other values (60) 18913
 
21.3%
None
ValueCountFrequency (%)
ó 1
50.0%
  1
50.0%

addr2
Text

Distinct523
Distinct (%)20.1%
Missing0
Missing (%)0.0%
Memory size314.8 KiB
2024-09-19T19:18:32.854006image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Length

Max length75
Median length75
Mean length74.971912
Min length2

Characters and Unicode

Total characters194852
Distinct characters70
Distinct categories8 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique387 ?
Unique (%)14.9%

Sample

1st row
2nd rowAmerican Association For Accreditation Of Ambulato
3rd rowSte 200
4th rowSte 307
5th rowSte B
ValueCountFrequency (%)
ste 571
 
20.7%
of 107
 
3.9%
health 53
 
1.9%
box 48
 
1.7%
po 40
 
1.5%
39
 
1.4%
fl 36
 
1.3%
verification 35
 
1.3%
200 33
 
1.2%
300 32
 
1.2%
Other values (634) 1764
64.0%
2024-09-19T19:18:33.627290image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
182652
93.7%
e 1300
 
0.7%
t 1070
 
0.5%
0 827
 
0.4%
i 779
 
0.4%
S 673
 
0.3%
o 635
 
0.3%
n 546
 
0.3%
a 514
 
0.3%
s 452
 
0.2%
Other values (60) 5404
 
2.8%

Most occurring categories

ValueCountFrequency (%)
Space Separator 182652
93.7%
Lowercase Letter 7667
 
3.9%
Decimal Number 2341
 
1.2%
Uppercase Letter 2012
 
1.0%
Other Punctuation 147
 
0.1%
Dash Punctuation 25
 
< 0.1%
Open Punctuation 4
 
< 0.1%
Close Punctuation 4
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 1300
17.0%
t 1070
14.0%
i 779
10.2%
o 635
8.3%
n 546
7.1%
a 514
 
6.7%
s 452
 
5.9%
r 391
 
5.1%
c 343
 
4.5%
l 298
 
3.9%
Other values (16) 1339
17.5%
Uppercase Letter
ValueCountFrequency (%)
S 673
33.4%
B 157
 
7.8%
O 156
 
7.8%
P 127
 
6.3%
C 121
 
6.0%
L 117
 
5.8%
D 106
 
5.3%
A 100
 
5.0%
H 79
 
3.9%
R 73
 
3.6%
Other values (14) 303
15.1%
Decimal Number
ValueCountFrequency (%)
0 827
35.3%
1 362
15.5%
2 241
 
10.3%
3 217
 
9.3%
5 183
 
7.8%
4 176
 
7.5%
6 111
 
4.7%
7 85
 
3.6%
8 73
 
3.1%
9 66
 
2.8%
Other Punctuation
ValueCountFrequency (%)
, 63
42.9%
/ 47
32.0%
# 22
 
15.0%
& 9
 
6.1%
. 5
 
3.4%
' 1
 
0.7%
Space Separator
ValueCountFrequency (%)
182652
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 25
100.0%
Open Punctuation
ValueCountFrequency (%)
( 4
100.0%
Close Punctuation
ValueCountFrequency (%)
) 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 185173
95.0%
Latin 9679
 
5.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 1300
13.4%
t 1070
 
11.1%
i 779
 
8.0%
S 673
 
7.0%
o 635
 
6.6%
n 546
 
5.6%
a 514
 
5.3%
s 452
 
4.7%
r 391
 
4.0%
c 343
 
3.5%
Other values (40) 2976
30.7%
Common
ValueCountFrequency (%)
182652
98.6%
0 827
 
0.4%
1 362
 
0.2%
2 241
 
0.1%
3 217
 
0.1%
5 183
 
0.1%
4 176
 
0.1%
6 111
 
0.1%
7 85
 
< 0.1%
8 73
 
< 0.1%
Other values (10) 246
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 194852
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
182652
93.7%
e 1300
 
0.7%
t 1070
 
0.5%
0 827
 
0.4%
i 779
 
0.4%
S 673
 
0.3%
o 635
 
0.3%
n 546
 
0.3%
a 514
 
0.3%
s 452
 
0.2%
Other values (60) 5404
 
2.8%

city
Text

Distinct437
Distinct (%)16.8%
Missing0
Missing (%)0.0%
Memory size200.7 KiB
2024-09-19T19:18:34.097578image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Length

Max length30
Median length30
Mean length30
Min length30

Characters and Unicode

Total characters77970
Distinct characters56
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique259 ?
Unique (%)10.0%

Sample

1st rowEast Orange
2nd rowGurnee
3rd rowSkokie
4th rowEast Providence
5th rowKimberly
ValueCountFrequency (%)
chicago 128
 
4.5%
city 97
 
3.4%
washington 70
 
2.4%
austin 48
 
1.7%
philadelphia 45
 
1.6%
tallahassee 39
 
1.4%
hill 38
 
1.3%
sacramento 37
 
1.3%
albany 34
 
1.2%
baltimore 34
 
1.2%
Other values (468) 2289
80.1%
2024-09-19T19:18:34.780125image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
58205
74.7%
a 1957
 
2.5%
e 1661
 
2.1%
n 1582
 
2.0%
o 1562
 
2.0%
i 1431
 
1.8%
l 1273
 
1.6%
r 989
 
1.3%
t 986
 
1.3%
s 951
 
1.2%
Other values (46) 7373
 
9.5%

Most occurring categories

ValueCountFrequency (%)
Space Separator 58206
74.7%
Lowercase Letter 16893
 
21.7%
Uppercase Letter 2864
 
3.7%
Other Punctuation 6
 
< 0.1%
Dash Punctuation 1
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a 1957
11.6%
e 1661
9.8%
n 1582
9.4%
o 1562
9.2%
i 1431
 
8.5%
l 1273
 
7.5%
r 989
 
5.9%
t 986
 
5.8%
s 951
 
5.6%
h 684
 
4.0%
Other values (17) 3817
22.6%
Uppercase Letter
ValueCountFrequency (%)
C 447
15.6%
S 285
 
10.0%
H 200
 
7.0%
B 197
 
6.9%
A 193
 
6.7%
L 183
 
6.4%
M 173
 
6.0%
P 167
 
5.8%
R 162
 
5.7%
D 139
 
4.9%
Other values (13) 718
25.1%
Other Punctuation
ValueCountFrequency (%)
, 3
50.0%
. 2
33.3%
' 1
 
16.7%
Space Separator
ValueCountFrequency (%)
58205
> 99.9%
  1
 
< 0.1%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 58213
74.7%
Latin 19757
 
25.3%

Most frequent character per script

Latin
ValueCountFrequency (%)
a 1957
 
9.9%
e 1661
 
8.4%
n 1582
 
8.0%
o 1562
 
7.9%
i 1431
 
7.2%
l 1273
 
6.4%
r 989
 
5.0%
t 986
 
5.0%
s 951
 
4.8%
h 684
 
3.5%
Other values (40) 6681
33.8%
Common
ValueCountFrequency (%)
58205
> 99.9%
, 3
 
< 0.1%
. 2
 
< 0.1%
- 1
 
< 0.1%
  1
 
< 0.1%
' 1
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 77968
> 99.9%
None 2
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
58205
74.7%
a 1957
 
2.5%
e 1661
 
2.1%
n 1582
 
2.0%
o 1562
 
2.0%
i 1431
 
1.8%
l 1273
 
1.6%
r 989
 
1.3%
t 986
 
1.3%
s 951
 
1.2%
Other values (44) 7371
 
9.5%
None
ValueCountFrequency (%)
  1
50.0%
ø 1
50.0%

state
Text

Distinct68
Distinct (%)2.6%
Missing0
Missing (%)0.0%
Memory size129.6 KiB
2024-09-19T19:18:35.157457image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Length

Max length2
Median length2
Mean length2
Min length2

Characters and Unicode

Total characters5198
Distinct characters27
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique9 ?
Unique (%)0.3%

Sample

1st rowNJ
2nd rowIL
3rd rowIL
4th rowRI
5th rowWI
ValueCountFrequency (%)
il 228
 
9.8%
md 100
 
4.3%
fl 98
 
4.2%
pa 84
 
3.6%
ca 83
 
3.6%
nc 82
 
3.5%
tx 82
 
3.5%
dc 70
 
3.0%
ny 59
 
2.5%
mi 57
 
2.5%
Other values (57) 1375
59.3%
2024-09-19T19:18:35.807010image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
562
10.8%
A 537
10.3%
N 468
 
9.0%
I 455
 
8.8%
M 411
 
7.9%
L 384
 
7.4%
C 337
 
6.5%
D 263
 
5.1%
O 221
 
4.3%
T 220
 
4.2%
Other values (17) 1340
25.8%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 4636
89.2%
Space Separator 562
 
10.8%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
A 537
11.6%
N 468
 
10.1%
I 455
 
9.8%
M 411
 
8.9%
L 384
 
8.3%
C 337
 
7.3%
D 263
 
5.7%
O 221
 
4.8%
T 220
 
4.7%
V 136
 
2.9%
Other values (16) 1204
26.0%
Space Separator
ValueCountFrequency (%)
562
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 4636
89.2%
Common 562
 
10.8%

Most frequent character per script

Latin
ValueCountFrequency (%)
A 537
11.6%
N 468
 
10.1%
I 455
 
9.8%
M 411
 
8.9%
L 384
 
8.3%
C 337
 
7.3%
D 263
 
5.7%
O 221
 
4.8%
T 220
 
4.7%
V 136
 
2.9%
Other values (16) 1204
26.0%
Common
ValueCountFrequency (%)
562
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 5198
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
562
10.8%
A 537
10.3%
N 468
 
9.0%
I 455
 
8.8%
M 411
 
7.9%
L 384
 
7.4%
C 337
 
6.5%
D 263
 
5.1%
O 221
 
4.3%
T 220
 
4.2%
Other values (17) 1340
25.8%

zip
Text

Distinct1161
Distinct (%)44.7%
Missing0
Missing (%)0.0%
Memory size145.2 KiB
2024-09-19T19:18:36.315176image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Length

Max length10
Median length10
Mean length8.1504425
Min length3

Characters and Unicode

Total characters21183
Distinct characters36
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique845 ?
Unique (%)32.5%

Sample

1st row07018-1023
2nd row60031
3rd row60077-4461
4th row02914-2012
5th row54136
ValueCountFrequency (%)
60611 34
 
1.5%
12234-1000 27
 
1.2%
27514-1692 22
 
1.0%
20002 22
 
1.0%
04333-0035 21
 
0.9%
96801 19
 
0.8%
19106-3699 17
 
0.7%
80202-5146 17
 
0.7%
46204 16
 
0.7%
60615-4379 16
 
0.7%
Other values (1168) 2064
90.7%
2024-09-19T19:18:37.065641image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
3527
16.7%
0 2756
13.0%
1 2270
10.7%
2 2061
9.7%
3 1583
7.5%
6 1431
6.8%
5 1424
6.7%
- 1294
 
6.1%
4 1278
 
6.0%
9 1206
 
5.7%
Other values (26) 2353
11.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 16219
76.6%
Space Separator 3527
 
16.7%
Dash Punctuation 1294
 
6.1%
Uppercase Letter 89
 
0.4%
Lowercase Letter 54
 
0.3%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
N 22
24.7%
A 9
10.1%
K 7
 
7.9%
E 6
 
6.7%
W 5
 
5.6%
J 5
 
5.6%
G 4
 
4.5%
L 4
 
4.5%
S 4
 
4.5%
M 3
 
3.4%
Other values (11) 20
22.5%
Decimal Number
ValueCountFrequency (%)
0 2756
17.0%
1 2270
14.0%
2 2061
12.7%
3 1583
9.8%
6 1431
8.8%
5 1424
8.8%
4 1278
7.9%
9 1206
7.4%
8 1120
6.9%
7 1090
 
6.7%
Lowercase Letter
ValueCountFrequency (%)
o 18
33.3%
n 18
33.3%
e 18
33.3%
Space Separator
ValueCountFrequency (%)
3527
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1294
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 21040
99.3%
Latin 143
 
0.7%

Most frequent character per script

Latin
ValueCountFrequency (%)
N 22
15.4%
o 18
12.6%
n 18
12.6%
e 18
12.6%
A 9
 
6.3%
K 7
 
4.9%
E 6
 
4.2%
W 5
 
3.5%
J 5
 
3.5%
G 4
 
2.8%
Other values (14) 31
21.7%
Common
ValueCountFrequency (%)
3527
16.8%
0 2756
13.1%
1 2270
10.8%
2 2061
9.8%
3 1583
7.5%
6 1431
6.8%
5 1424
6.8%
- 1294
 
6.2%
4 1278
 
6.1%
9 1206
 
5.7%
Other values (2) 2210
10.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 21183
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
3527
16.7%
0 2756
13.0%
1 2270
10.7%
2 2061
9.7%
3 1583
7.5%
6 1431
6.8%
5 1424
6.7%
- 1294
 
6.1%
4 1278
 
6.0%
9 1206
 
5.7%
Other values (26) 2353
11.1%

phone
Text

Distinct1249
Distinct (%)48.1%
Missing0
Missing (%)0.0%
Memory size160.0 KiB
2024-09-19T19:18:37.595974image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Length

Max length14
Median length14
Mean length13.990766
Min length11

Characters and Unicode

Total characters36362
Distinct characters17
Distinct categories8 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1016 ?
Unique (%)39.1%

Sample

1st row
2nd row(847) 775-1970
3rd row(847) 853-6060
4th row(401) 524-3076
5th row(920) 560-5631
ValueCountFrequency (%)
800 102
 
2.7%
312 63
 
1.7%
919 50
 
1.3%
847 46
 
1.2%
877 44
 
1.2%
215 41
 
1.1%
512 37
 
1.0%
617 33
 
0.9%
850 32
 
0.8%
518 31
 
0.8%
Other values (1430) 3305
87.3%
2024-09-19T19:18:38.345385image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
11552
31.8%
0 2608
 
7.2%
2 2259
 
6.2%
7 2048
 
5.6%
8 1955
 
5.4%
- 1909
 
5.2%
) 1897
 
5.2%
( 1897
 
5.2%
6 1845
 
5.1%
4 1844
 
5.1%
Other values (7) 6548
18.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 19094
52.5%
Space Separator 11552
31.8%
Dash Punctuation 1909
 
5.2%
Close Punctuation 1897
 
5.2%
Open Punctuation 1897
 
5.2%
Other Punctuation 5
 
< 0.1%
Uppercase Letter 4
 
< 0.1%
Math Symbol 4
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 2608
13.7%
2 2259
11.8%
7 2048
10.7%
8 1955
10.2%
6 1845
9.7%
4 1844
9.7%
5 1821
9.5%
1 1757
9.2%
3 1707
8.9%
9 1250
6.5%
Space Separator
ValueCountFrequency (%)
11552
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1909
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1897
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1897
100.0%
Other Punctuation
ValueCountFrequency (%)
. 5
100.0%
Uppercase Letter
ValueCountFrequency (%)
E 4
100.0%
Math Symbol
ValueCountFrequency (%)
+ 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 36358
> 99.9%
Latin 4
 
< 0.1%

Most frequent character per script

Common
ValueCountFrequency (%)
11552
31.8%
0 2608
 
7.2%
2 2259
 
6.2%
7 2048
 
5.6%
8 1955
 
5.4%
- 1909
 
5.3%
) 1897
 
5.2%
( 1897
 
5.2%
6 1845
 
5.1%
4 1844
 
5.1%
Other values (6) 6544
18.0%
Latin
ValueCountFrequency (%)
E 4
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 36362
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
11552
31.8%
0 2608
 
7.2%
2 2259
 
6.2%
7 2048
 
5.6%
8 1955
 
5.4%
- 1909
 
5.2%
) 1897
 
5.2%
( 1897
 
5.2%
6 1845
 
5.1%
4 1844
 
5.1%
Other values (7) 6548
18.0%

contact1
Text

Distinct66
Distinct (%)2.5%
Missing0
Missing (%)0.0%
Memory size378.3 KiB
2024-09-19T19:18:38.893703image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Length

Max length100
Median length100
Mean length100
Min length100

Characters and Unicode

Total characters259900
Distinct characters71
Distinct categories9 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique63 ?
Unique (%)2.4%

Sample

1st row
2nd row
3rd row
4th row
5th row
ValueCountFrequency (%)
attn 14
 
6.3%
verification 10
 
4.5%
specialist 7
 
3.2%
of 6
 
2.7%
and 4
 
1.8%
license 3
 
1.4%
education 3
 
1.4%
office 3
 
1.4%
director 3
 
1.4%
3
 
1.4%
Other values (148) 165
74.7%
2024-09-19T19:18:39.634166image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
258019
99.3%
e 181
 
0.1%
i 157
 
0.1%
t 148
 
0.1%
n 135
 
0.1%
a 121
 
< 0.1%
o 117
 
< 0.1%
r 114
 
< 0.1%
c 90
 
< 0.1%
s 75
 
< 0.1%
Other values (61) 743
 
0.3%

Most occurring categories

ValueCountFrequency (%)
Space Separator 258019
99.3%
Lowercase Letter 1500
 
0.6%
Uppercase Letter 225
 
0.1%
Other Punctuation 110
 
< 0.1%
Decimal Number 28
 
< 0.1%
Dash Punctuation 9
 
< 0.1%
Open Punctuation 3
 
< 0.1%
Close Punctuation 3
 
< 0.1%
Currency Symbol 3
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 181
12.1%
i 157
10.5%
t 148
9.9%
n 135
9.0%
a 121
 
8.1%
o 117
 
7.8%
r 114
 
7.6%
c 90
 
6.0%
s 75
 
5.0%
l 54
 
3.6%
Other values (15) 308
20.5%
Uppercase Letter
ValueCountFrequency (%)
A 29
12.9%
D 23
10.2%
S 20
 
8.9%
L 18
 
8.0%
V 17
 
7.6%
C 17
 
7.6%
P 14
 
6.2%
R 13
 
5.8%
E 10
 
4.4%
O 10
 
4.4%
Other values (13) 54
24.0%
Other Punctuation
ValueCountFrequency (%)
/ 35
31.8%
. 31
28.2%
: 25
22.7%
, 10
 
9.1%
" 4
 
3.6%
@ 2
 
1.8%
' 1
 
0.9%
# 1
 
0.9%
; 1
 
0.9%
Decimal Number
ValueCountFrequency (%)
5 6
21.4%
7 4
14.3%
2 4
14.3%
0 4
14.3%
8 3
10.7%
9 3
10.7%
4 2
 
7.1%
3 1
 
3.6%
1 1
 
3.6%
Space Separator
ValueCountFrequency (%)
258019
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 9
100.0%
Open Punctuation
ValueCountFrequency (%)
( 3
100.0%
Close Punctuation
ValueCountFrequency (%)
) 3
100.0%
Currency Symbol
ValueCountFrequency (%)
$ 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 258175
99.3%
Latin 1725
 
0.7%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 181
 
10.5%
i 157
 
9.1%
t 148
 
8.6%
n 135
 
7.8%
a 121
 
7.0%
o 117
 
6.8%
r 114
 
6.6%
c 90
 
5.2%
s 75
 
4.3%
l 54
 
3.1%
Other values (38) 533
30.9%
Common
ValueCountFrequency (%)
258019
99.9%
/ 35
 
< 0.1%
. 31
 
< 0.1%
: 25
 
< 0.1%
, 10
 
< 0.1%
- 9
 
< 0.1%
5 6
 
< 0.1%
7 4
 
< 0.1%
2 4
 
< 0.1%
" 4
 
< 0.1%
Other values (13) 28
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 259900
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
258019
99.3%
e 181
 
0.1%
i 157
 
0.1%
t 148
 
0.1%
n 135
 
0.1%
a 121
 
< 0.1%
o 117
 
< 0.1%
r 114
 
< 0.1%
c 90
 
< 0.1%
s 75
 
< 0.1%
Other values (61) 743
 
0.3%

nation
Categorical

IMBALANCE 

Distinct29
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Memory size175.3 KiB
1567 
United States
906 
USA
 
60
Canada
 
24
United Kingdom
 
7
Other values (24)
 
35

Length

Max length20
Median length20
Mean length20
Min length20

Characters and Unicode

Total characters51980
Distinct characters45
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique17 ?
Unique (%)0.7%

Sample

1st rowUnited States
2nd row
3rd row
4th rowUnited States
5th rowUnited States

Common Values

ValueCountFrequency (%)
1567
60.3%
United States 906
34.9%
USA 60
 
2.3%
Canada 24
 
0.9%
United Kingdom 7
 
0.3%
India 3
 
0.1%
Japan 3
 
0.1%
United States of Ame 3
 
0.1%
Australia 3
 
0.1%
Jordan 2
 
0.1%
Other values (19) 21
 
0.8%

Length

2024-09-19T19:18:39.879531image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
united 917
46.7%
states 911
46.4%
usa 60
 
3.1%
canada 24
 
1.2%
kingdom 7
 
0.4%
india 3
 
0.2%
japan 3
 
0.2%
of 3
 
0.2%
ame 3
 
0.2%
australia 3
 
0.2%
Other values (27) 30
 
1.5%

Most occurring characters

ValueCountFrequency (%)
40394
77.7%
t 2750
 
5.3%
e 1839
 
3.5%
a 1018
 
2.0%
U 981
 
1.9%
S 975
 
1.9%
n 969
 
1.9%
d 962
 
1.9%
i 936
 
1.8%
s 915
 
1.8%
Other values (35) 241
 
0.5%

Most occurring categories

ValueCountFrequency (%)
Space Separator 40394
77.7%
Lowercase Letter 9481
 
18.2%
Uppercase Letter 2079
 
4.0%
Decimal Number 20
 
< 0.1%
Open Punctuation 2
 
< 0.1%
Close Punctuation 2
 
< 0.1%
Dash Punctuation 2
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
t 2750
29.0%
e 1839
19.4%
a 1018
 
10.7%
n 969
 
10.2%
d 962
 
10.1%
i 936
 
9.9%
s 915
 
9.7%
o 20
 
0.2%
m 15
 
0.2%
g 11
 
0.1%
Other values (9) 46
 
0.5%
Uppercase Letter
ValueCountFrequency (%)
U 981
47.2%
S 975
46.9%
A 67
 
3.2%
C 25
 
1.2%
K 8
 
0.4%
J 5
 
0.2%
I 4
 
0.2%
G 4
 
0.2%
B 2
 
0.1%
N 2
 
0.1%
Other values (5) 6
 
0.3%
Decimal Number
ValueCountFrequency (%)
8 4
20.0%
5 4
20.0%
0 4
20.0%
4 4
20.0%
2 2
10.0%
6 1
 
5.0%
7 1
 
5.0%
Space Separator
ValueCountFrequency (%)
40394
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 40420
77.8%
Latin 11560
 
22.2%

Most frequent character per script

Latin
ValueCountFrequency (%)
t 2750
23.8%
e 1839
15.9%
a 1018
 
8.8%
U 981
 
8.5%
S 975
 
8.4%
n 969
 
8.4%
d 962
 
8.3%
i 936
 
8.1%
s 915
 
7.9%
A 67
 
0.6%
Other values (24) 148
 
1.3%
Common
ValueCountFrequency (%)
40394
99.9%
8 4
 
< 0.1%
5 4
 
< 0.1%
0 4
 
< 0.1%
4 4
 
< 0.1%
( 2
 
< 0.1%
) 2
 
< 0.1%
2 2
 
< 0.1%
- 2
 
< 0.1%
6 1
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 51980
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
40394
77.7%
t 2750
 
5.3%
e 1839
 
3.5%
a 1018
 
2.0%
U 981
 
1.9%
S 975
 
1.9%
n 969
 
1.9%
d 962
 
1.9%
i 936
 
1.8%
s 915
 
1.8%
Other values (35) 241
 
0.5%

fax
Text

Distinct514
Distinct (%)19.8%
Missing0
Missing (%)0.0%
Memory size160.0 KiB
2024-09-19T19:18:40.365938image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Length

Max length14
Median length14
Mean length13.996537
Min length5

Characters and Unicode

Total characters36377
Distinct characters14
Distinct categories5 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique426 ?
Unique (%)16.4%

Sample

1st row
2nd row(847) 775-1985
3rd row(847) 853-9028
4th row
5th row
ValueCountFrequency (%)
847 31
 
2.1%
215 21
 
1.4%
919 19
 
1.3%
312 18
 
1.2%
801 18
 
1.2%
18
 
1.2%
202 17
 
1.2%
512 17
 
1.2%
446-3470 17
 
1.2%
916 16
 
1.1%
Other values (639) 1275
86.9%
2024-09-19T19:18:41.109735image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
26831
73.8%
2 898
 
2.5%
7 842
 
2.3%
0 782
 
2.1%
5 776
 
2.1%
- 744
 
2.0%
6 738
 
2.0%
) 734
 
2.0%
( 733
 
2.0%
1 721
 
2.0%
Other values (4) 2578
 
7.1%

Most occurring categories

ValueCountFrequency (%)
Space Separator 26831
73.8%
Decimal Number 7335
 
20.2%
Dash Punctuation 744
 
2.0%
Close Punctuation 734
 
2.0%
Open Punctuation 733
 
2.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 898
12.2%
7 842
11.5%
0 782
10.7%
5 776
10.6%
6 738
10.1%
1 721
9.8%
4 694
9.5%
3 688
9.4%
8 656
8.9%
9 540
7.4%
Space Separator
ValueCountFrequency (%)
26831
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 744
100.0%
Close Punctuation
ValueCountFrequency (%)
) 734
100.0%
Open Punctuation
ValueCountFrequency (%)
( 733
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 36377
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
26831
73.8%
2 898
 
2.5%
7 842
 
2.3%
0 782
 
2.1%
5 776
 
2.1%
- 744
 
2.0%
6 738
 
2.0%
) 734
 
2.0%
( 733
 
2.0%
1 721
 
2.0%
Other values (4) 2578
 
7.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 36377
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
26831
73.8%
2 898
 
2.5%
7 842
 
2.3%
0 782
 
2.1%
5 776
 
2.1%
- 744
 
2.0%
6 738
 
2.0%
) 734
 
2.0%
( 733
 
2.0%
1 721
 
2.0%
Other values (4) 2578
 
7.1%

cvo_type
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size132.1 KiB
2599 

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters7797
Distinct characters1
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row
2nd row
3rd row
4th row
5th row

Common Values

ValueCountFrequency (%)
2599
100.0%

Length

2024-09-19T19:18:41.373704image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-09-19T19:18:41.543027image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
7797
100.0%

Most occurring categories

ValueCountFrequency (%)
Space Separator 7797
100.0%

Most frequent character per category

Space Separator
ValueCountFrequency (%)
7797
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 7797
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
7797
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 7797
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
7797
100.0%

homehtml
Text

MISSING 

Distinct845
Distinct (%)54.9%
Missing1059
Missing (%)40.7%
Memory size186.3 KiB
2024-09-19T19:18:41.898283image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Length

Max length167
Median length95
Mean length52.216883
Min length9

Characters and Unicode

Total characters80414
Distinct characters85
Distinct categories11 ?
Distinct scripts2 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique725 ?
Unique (%)47.1%

Sample

1st rowhttp://www.aaahc.org
2nd rowwww.aabronchology.org
3rd rowhttps://americanacademy.org/
4th rowhttps://www.aacn.org/dm/CustomerProfile/Login.aspx?mid=2869&
5th rowhttps://www.diabeteseducator.org/practice/diabetes-education-accreditation-program
ValueCountFrequency (%)
https://aoaprofiles.org 95
 
6.7%
http://www.op.nysed.gov/opsearches.htm 23
 
1.6%
https://fortress.wa.gov/doh/providercredentialsearch 22
 
1.6%
http://www.abp.org 21
 
1.5%
http://pvl.ehawaii.gov/pvlsearch/app 18
 
1.3%
https://www.medicaid.gov/about-us/contact-us/index.html 17
 
1.2%
https://appsmqa.doh.state.fl.us/mqasearchservices/healthcareproviders 16
 
1.1%
https://ebiz.mt.gov/pol/generalproperty/propertylookup.aspx?islicensee=y&tabname=apo 16
 
1.1%
https://apps.health.tn.gov/licensure 14
 
1.0%
https://www.nursingworld.org/certification/verification 12
 
0.9%
Other values (842) 1154
82.0%
2024-09-19T19:18:42.657003image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
19140
23.8%
/ 5264
 
6.5%
t 4773
 
5.9%
e 3916
 
4.9%
s 3820
 
4.8%
. 3611
 
4.5%
o 3594
 
4.5%
a 3473
 
4.3%
p 3171
 
3.9%
r 2841
 
3.5%
Other values (75) 26811
33.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 47877
59.5%
Space Separator 19149
 
23.8%
Other Punctuation 10441
 
13.0%
Uppercase Letter 1902
 
2.4%
Dash Punctuation 407
 
0.5%
Decimal Number 366
 
0.5%
Math Symbol 140
 
0.2%
Connector Punctuation 126
 
0.2%
Currency Symbol 2
 
< 0.1%
Open Punctuation 2
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
t 4773
 
10.0%
e 3916
 
8.2%
s 3820
 
8.0%
o 3594
 
7.5%
a 3473
 
7.3%
p 3171
 
6.6%
r 2841
 
5.9%
i 2823
 
5.9%
h 2527
 
5.3%
c 2472
 
5.2%
Other values (16) 14467
30.2%
Uppercase Letter
ValueCountFrequency (%)
L 339
17.8%
P 227
11.9%
S 217
11.4%
A 139
 
7.3%
O 103
 
5.4%
C 89
 
4.7%
I 86
 
4.5%
M 83
 
4.4%
B 78
 
4.1%
D 65
 
3.4%
Other values (16) 476
25.0%
Other Punctuation
ValueCountFrequency (%)
/ 5264
50.4%
. 3611
34.6%
: 1357
 
13.0%
? 94
 
0.9%
& 45
 
0.4%
# 36
 
0.3%
% 25
 
0.2%
, 4
 
< 0.1%
* 1
 
< 0.1%
! 1
 
< 0.1%
Other values (3) 3
 
< 0.1%
Decimal Number
ValueCountFrequency (%)
2 70
19.1%
0 70
19.1%
1 60
16.4%
3 34
9.3%
4 30
8.2%
5 27
 
7.4%
7 22
 
6.0%
8 20
 
5.5%
9 19
 
5.2%
6 14
 
3.8%
Math Symbol
ValueCountFrequency (%)
= 132
94.3%
+ 6
 
4.3%
| 2
 
1.4%
Space Separator
ValueCountFrequency (%)
19140
> 99.9%
  9
 
< 0.1%
Dash Punctuation
ValueCountFrequency (%)
- 407
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 126
100.0%
Currency Symbol
ValueCountFrequency (%)
$ 2
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 49779
61.9%
Common 30635
38.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
t 4773
 
9.6%
e 3916
 
7.9%
s 3820
 
7.7%
o 3594
 
7.2%
a 3473
 
7.0%
p 3171
 
6.4%
r 2841
 
5.7%
i 2823
 
5.7%
h 2527
 
5.1%
c 2472
 
5.0%
Other values (42) 16369
32.9%
Common
ValueCountFrequency (%)
19140
62.5%
/ 5264
 
17.2%
. 3611
 
11.8%
: 1357
 
4.4%
- 407
 
1.3%
= 132
 
0.4%
_ 126
 
0.4%
? 94
 
0.3%
2 70
 
0.2%
0 70
 
0.2%
Other values (23) 364
 
1.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 80404
> 99.9%
None 9
 
< 0.1%
Punctuation 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
19140
23.8%
/ 5264
 
6.5%
t 4773
 
5.9%
e 3916
 
4.9%
s 3820
 
4.8%
. 3611
 
4.5%
o 3594
 
4.5%
a 3473
 
4.3%
p 3171
 
3.9%
r 2841
 
3.5%
Other values (73) 26801
33.3%
None
ValueCountFrequency (%)
  9
100.0%
Punctuation
ValueCountFrequency (%)
… 1
100.0%

ver_elec
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size127.0 KiB
0
1442 
1
1157 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters2599
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row1
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 1442
55.5%
1 1157
44.5%

Length

2024-09-19T19:18:43.164397image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-09-19T19:18:43.373409image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
ValueCountFrequency (%)
0 1442
55.5%
1 1157
44.5%

Most occurring characters

ValueCountFrequency (%)
0 1442
55.5%
1 1157
44.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2599
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 1442
55.5%
1 1157
44.5%

Most occurring scripts

ValueCountFrequency (%)
Common 2599
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 1442
55.5%
1 1157
44.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2599
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 1442
55.5%
1 1157
44.5%

newcd
Text

Distinct54
Distinct (%)2.1%
Missing0
Missing (%)0.0%
Memory size139.3 KiB
2024-09-19T19:18:43.724690image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Length

Max length6
Median length6
Mean length5.8372451
Min length1

Characters and Unicode

Total characters15171
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique5 ?
Unique (%)0.2%

Sample

1st row
2nd row
3rd row
4th row
5th row
ValueCountFrequency (%)
10 3
 
2.9%
34 2
 
2.0%
13 2
 
2.0%
4 2
 
2.0%
3 2
 
2.0%
6 2
 
2.0%
7 2
 
2.0%
9 2
 
2.0%
8 2
 
2.0%
11 2
 
2.0%
Other values (43) 81
79.4%
2024-09-19T19:18:44.333510image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
14982
98.8%
1 32
 
0.2%
3 32
 
0.2%
4 30
 
0.2%
2 27
 
0.2%
5 15
 
0.1%
6 12
 
0.1%
0 11
 
0.1%
8 10
 
0.1%
9 10
 
0.1%

Most occurring categories

ValueCountFrequency (%)
Space Separator 14982
98.8%
Decimal Number 189
 
1.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 32
16.9%
3 32
16.9%
4 30
15.9%
2 27
14.3%
5 15
7.9%
6 12
 
6.3%
0 11
 
5.8%
8 10
 
5.3%
9 10
 
5.3%
7 10
 
5.3%
Space Separator
ValueCountFrequency (%)
14982
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 15171
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
14982
98.8%
1 32
 
0.2%
3 32
 
0.2%
4 30
 
0.2%
2 27
 
0.2%
5 15
 
0.1%
6 12
 
0.1%
0 11
 
0.1%
8 10
 
0.1%
9 10
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 15171
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
14982
98.8%
1 32
 
0.2%
3 32
 
0.2%
4 30
 
0.2%
2 27
 
0.2%
5 15
 
0.1%
6 12
 
0.1%
0 11
 
0.1%
8 10
 
0.1%
9 10
 
0.1%

email
Text

Distinct265
Distinct (%)10.2%
Missing0
Missing (%)0.0%
Memory size378.3 KiB
2024-09-19T19:18:44.806379image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Length

Max length100
Median length100
Mean length100
Min length100

Characters and Unicode

Total characters259900
Distinct characters67
Distinct categories10 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique251 ?
Unique (%)9.7%

Sample

1st row
2nd row
3rd rowinfo@aaahc.org
4th row
5th rowinfo@aabiom.com
ValueCountFrequency (%)
abpeds@abpeds.org 17
 
5.7%
communications@abderm.org 5
 
1.7%
alliedhealth@mass.gov 3
 
1.0%
kelli.hood@aaphc.org 3
 
1.0%
general@abfp.org 3
 
1.0%
abai@abai.org 2
 
0.7%
francesca.reyes@catalight.org 2
 
0.7%
specialtycaq@nccpa.net 2
 
0.7%
linda@dentalboard.org 2
 
0.7%
tacc@asts.org 2
 
0.7%
Other values (254) 259
86.3%
2024-09-19T19:18:45.571151image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
253844
97.7%
o 555
 
0.2%
a 541
 
0.2%
. 417
 
0.2%
r 377
 
0.1%
s 343
 
0.1%
e 335
 
0.1%
c 334
 
0.1%
i 318
 
0.1%
n 316
 
0.1%
Other values (57) 2520
 
1.0%

Most occurring categories

ValueCountFrequency (%)
Space Separator 253844
97.7%
Lowercase Letter 5108
 
2.0%
Other Punctuation 724
 
0.3%
Uppercase Letter 185
 
0.1%
Decimal Number 22
 
< 0.1%
Dash Punctuation 11
 
< 0.1%
Connector Punctuation 3
 
< 0.1%
Currency Symbol 1
 
< 0.1%
Close Punctuation 1
 
< 0.1%
Open Punctuation 1
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o 555
 
10.9%
a 541
 
10.6%
r 377
 
7.4%
s 343
 
6.7%
e 335
 
6.6%
c 334
 
6.5%
i 318
 
6.2%
n 316
 
6.2%
g 272
 
5.3%
t 269
 
5.3%
Other values (16) 1448
28.3%
Uppercase Letter
ValueCountFrequency (%)
A 27
14.6%
C 25
13.5%
B 21
11.4%
D 19
10.3%
P 13
 
7.0%
S 11
 
5.9%
M 9
 
4.9%
R 8
 
4.3%
T 6
 
3.2%
F 5
 
2.7%
Other values (13) 41
22.2%
Decimal Number
ValueCountFrequency (%)
1 5
22.7%
4 4
18.2%
5 4
18.2%
3 3
13.6%
2 2
 
9.1%
7 2
 
9.1%
8 1
 
4.5%
0 1
 
4.5%
Other Punctuation
ValueCountFrequency (%)
. 417
57.6%
@ 293
40.5%
/ 11
 
1.5%
: 3
 
0.4%
Space Separator
ValueCountFrequency (%)
253844
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 11
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 3
100.0%
Currency Symbol
ValueCountFrequency (%)
$ 1
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 254607
98.0%
Latin 5293
 
2.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
o 555
 
10.5%
a 541
 
10.2%
r 377
 
7.1%
s 343
 
6.5%
e 335
 
6.3%
c 334
 
6.3%
i 318
 
6.0%
n 316
 
6.0%
g 272
 
5.1%
t 269
 
5.1%
Other values (39) 1633
30.9%
Common
ValueCountFrequency (%)
253844
99.7%
. 417
 
0.2%
@ 293
 
0.1%
- 11
 
< 0.1%
/ 11
 
< 0.1%
1 5
 
< 0.1%
4 4
 
< 0.1%
5 4
 
< 0.1%
_ 3
 
< 0.1%
3 3
 
< 0.1%
Other values (8) 12
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 259900
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
253844
97.7%
o 555
 
0.2%
a 541
 
0.2%
. 417
 
0.2%
r 377
 
0.1%
s 343
 
0.1%
e 335
 
0.1%
c 334
 
0.1%
i 318
 
0.1%
n 316
 
0.1%
Other values (57) 2520
 
1.0%

payfee
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct20
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.3579492
Minimum0
Maximum50
Zeros2369
Zeros (%)91.2%
Negative0
Negative (%)0.0%
Memory size20.4 KiB
2024-09-19T19:18:45.848910image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile17
Maximum50
Range50
Interquartile range (IQR)0

Descriptive statistics

Standard deviation5.7373552
Coefficient of variation (CV)4.2250146
Kurtosis31.91851
Mean1.3579492
Median Absolute Deviation (MAD)0
Skewness5.2336327
Sum3529.31
Variance32.917245
MonotonicityNot monotonic
2024-09-19T19:18:46.079693image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=20)
ValueCountFrequency (%)
0 2369
91.2%
17 96
 
3.7%
0.88 34
 
1.3%
0.97 17
 
0.7%
25 16
 
0.6%
0.01 12
 
0.5%
20 11
 
0.4%
50 11
 
0.4%
10 7
 
0.3%
15 6
 
0.2%
Other values (10) 20
 
0.8%
ValueCountFrequency (%)
0 2369
91.2%
0.01 12
 
0.5%
0.3 1
 
< 0.1%
0.88 34
 
1.3%
0.97 17
 
0.7%
0.98 1
 
< 0.1%
5 2
 
0.1%
8 2
 
0.1%
10 7
 
0.3%
11.5 1
 
< 0.1%
ValueCountFrequency (%)
50 11
 
0.4%
45 2
 
0.1%
42 1
 
< 0.1%
40 4
 
0.2%
35 2
 
0.1%
30 4
 
0.2%
25 16
 
0.6%
20 11
 
0.4%
17 96
3.7%
15 6
 
0.2%

link
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct2599
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1637088
Minimum1634040
Maximum1638443
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size20.4 KiB
2024-09-19T19:18:46.340149image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Quantile statistics

Minimum1634040
5-th percentile1635900.9
Q11636425.5
median1637077
Q31637727.5
95-th percentile1638313.1
Maximum1638443
Range4403
Interquartile range (IQR)1302

Descriptive statistics

Standard deviation771.66043
Coefficient of variation (CV)0.00047136161
Kurtosis-1.09804
Mean1637088
Median Absolute Deviation (MAD)651
Skewness0.025943476
Sum4.2547917 × 109
Variance595459.81
MonotonicityNot monotonic
2024-09-19T19:18:46.625452image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1634040 1
 
< 0.1%
1636644 1
 
< 0.1%
1636633 1
 
< 0.1%
1636634 1
 
< 0.1%
1636635 1
 
< 0.1%
1636636 1
 
< 0.1%
1637409 1
 
< 0.1%
1636637 1
 
< 0.1%
1636638 1
 
< 0.1%
1636639 1
 
< 0.1%
Other values (2589) 2589
99.6%
ValueCountFrequency (%)
1634040 1
< 0.1%
1635772 1
< 0.1%
1635773 1
< 0.1%
1635774 1
< 0.1%
1635775 1
< 0.1%
1635776 1
< 0.1%
1635777 1
< 0.1%
1635778 1
< 0.1%
1635779 1
< 0.1%
1635780 1
< 0.1%
ValueCountFrequency (%)
1638443 1
< 0.1%
1638442 1
< 0.1%
1638441 1
< 0.1%
1638440 1
< 0.1%
1638439 1
< 0.1%
1638438 1
< 0.1%
1638437 1
< 0.1%
1638436 1
< 0.1%
1638435 1
< 0.1%
1638434 1
< 0.1%

autofax
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size127.0 KiB
0
1448 
1
1151 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters2599
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1
2nd row1
3rd row0
4th row0
5th row1

Common Values

ValueCountFrequency (%)
0 1448
55.7%
1 1151
44.3%

Length

2024-09-19T19:18:46.875484image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-09-19T19:18:47.058130image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
ValueCountFrequency (%)
0 1448
55.7%
1 1151
44.3%

Most occurring characters

ValueCountFrequency (%)
0 1448
55.7%
1 1151
44.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2599
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 1448
55.7%
1 1151
44.3%

Most occurring scripts

ValueCountFrequency (%)
Common 2599
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 1448
55.7%
1 1151
44.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2599
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 1448
55.7%
1 1151
44.3%

autoemail
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size127.0 KiB
0
1449 
1
1150 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters2599
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1
2nd row0
3rd row0
4th row0
5th row1

Common Values

ValueCountFrequency (%)
0 1449
55.8%
1 1150
44.2%

Length

2024-09-19T19:18:47.252172image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-09-19T19:18:47.438011image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
ValueCountFrequency (%)
0 1449
55.8%
1 1150
44.2%

Most occurring characters

ValueCountFrequency (%)
0 1449
55.8%
1 1150
44.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2599
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 1449
55.8%
1 1150
44.2%

Most occurring scripts

ValueCountFrequency (%)
Common 2599
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 1449
55.8%
1 1150
44.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2599
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 1449
55.8%
1 1150
44.2%

latitude
Real number (ℝ)

HIGH CORRELATION  MISSING  ZEROS 

Distinct78
Distinct (%)34.8%
Missing2375
Missing (%)91.4%
Infinite0
Infinite (%)0.0%
Mean19423407
Minimum0
Maximum58301600
Zeros111
Zeros (%)4.3%
Negative0
Negative (%)0.0%
Memory size20.4 KiB
2024-09-19T19:18:47.676099image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median25295758
Q339066577
95-th percentile43213778
Maximum58301600
Range58301600
Interquartile range (IQR)39066577

Descriptive statistics

Standard deviation19625673
Coefficient of variation (CV)1.0104135
Kurtosis-1.8603692
Mean19423407
Median Absolute Deviation (MAD)25295758
Skewness0.085232314
Sum4.3508431 × 109
Variance3.8516703 × 1014
MonotonicityNot monotonic
2024-09-19T19:18:47.982125image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 111
 
4.3%
38576400 7
 
0.3%
39171467 6
 
0.2%
30318006 5
 
0.2%
35659931 5
 
0.2%
39356306 5
 
0.2%
37600145 3
 
0.1%
40273600 3
 
0.1%
33447469 3
 
0.1%
45528540 2
 
0.1%
Other values (68) 74
 
2.8%
(Missing) 2375
91.4%
ValueCountFrequency (%)
0 111
4.3%
20855859 1
 
< 0.1%
29735658 1
 
< 0.1%
29954500 1
 
< 0.1%
30266900 2
 
0.1%
30318006 5
 
0.2%
30331800 1
 
< 0.1%
32074307 1
 
< 0.1%
32333045 2
 
0.1%
32333445 1
 
< 0.1%
ValueCountFrequency (%)
58301600 2
0.1%
46874636 1
< 0.1%
45528540 2
0.1%
45512392 1
< 0.1%
45512240 1
< 0.1%
44943641 1
< 0.1%
44925238 1
< 0.1%
43534075 1
< 0.1%
43214076 1
< 0.1%
43213778 2
0.1%

longitude
Real number (ℝ)

HIGH CORRELATION  MISSING  ZEROS 

Distinct78
Distinct (%)34.8%
Missing2375
Missing (%)91.4%
Infinite0
Infinite (%)0.0%
Mean-23473674
Minimum-1.5631479 × 108
Maximum1.344194 × 108
Zeros111
Zeros (%)4.3%
Negative85
Negative (%)3.3%
Memory size20.4 KiB
2024-09-19T19:18:48.257643image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Quantile statistics

Minimum-1.5631479 × 108
5-th percentile-1.1733466 × 108
Q1-77514407
median0
Q30
95-th percentile92173600
Maximum1.344194 × 108
Range2.9073419 × 108
Interquartile range (IQR)77514407

Descriptive statistics

Standard deviation63237800
Coefficient of variation (CV)-2.6939881
Kurtosis-0.44152887
Mean-23473674
Median Absolute Deviation (MAD)71484850
Skewness0.27290371
Sum-5.258103 × 109
Variance3.9990193 × 1015
MonotonicityNot monotonic
2024-09-19T19:18:48.537414image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 111
 
4.3%
92173600 7
 
0.3%
-75536301 6
 
0.2%
-97734983 5
 
0.2%
-105982677 5
 
0.2%
-76702793 5
 
0.2%
-77514407 3
 
0.1%
76884700 3
 
0.1%
-112098022 3
 
0.1%
-122657406 2
 
0.1%
Other values (68) 74
 
2.8%
(Missing) 2375
91.4%
ValueCountFrequency (%)
-156314794 1
< 0.1%
-123027707 1
< 0.1%
-122994048 1
< 0.1%
-122679425 1
< 0.1%
-122676106 1
< 0.1%
-122657406 2
0.1%
-121499466 1
< 0.1%
-121415264 1
< 0.1%
-119789323 1
< 0.1%
-119750966 1
< 0.1%
ValueCountFrequency (%)
134419400 2
 
0.1%
121529500 1
 
< 0.1%
119766700 1
 
< 0.1%
119630200 1
 
< 0.1%
105937200 1
 
< 0.1%
97742800 2
 
0.1%
94644100 1
 
< 0.1%
92173600 7
0.3%
90075300 1
 
< 0.1%
89401200 1
 
< 0.1%

inactive
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size127.0 KiB
0
2545 
1
 
54

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters2599
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 2545
97.9%
1 54
 
2.1%

Length

2024-09-19T19:18:48.816503image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-09-19T19:18:48.996460image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
ValueCountFrequency (%)
0 2545
97.9%
1 54
 
2.1%

Most occurring characters

ValueCountFrequency (%)
0 2545
97.9%
1 54
 
2.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2599
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 2545
97.9%
1 54
 
2.1%

Most occurring scripts

ValueCountFrequency (%)
Common 2599
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 2545
97.9%
1 54
 
2.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2599
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 2545
97.9%
1 54
 
2.1%

extension
Text

MISSING 

Distinct4
Distinct (%)100.0%
Missing2595
Missing (%)99.8%
Memory size81.4 KiB
2024-09-19T19:18:49.198990image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Length

Max length5
Median length4.5
Mean length3.75
Min length3

Characters and Unicode

Total characters15
Distinct characters9
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique4 ?
Unique (%)100.0%

Sample

1st row2000
2nd row592
3rd row250
4th rowOpt 1
ValueCountFrequency (%)
2000 1
20.0%
592 1
20.0%
250 1
20.0%
opt 1
20.0%
1 1
20.0%
2024-09-19T19:18:49.705246image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 4
26.7%
2 3
20.0%
5 2
13.3%
9 1
 
6.7%
O 1
 
6.7%
p 1
 
6.7%
t 1
 
6.7%
1
 
6.7%
1 1
 
6.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 11
73.3%
Lowercase Letter 2
 
13.3%
Uppercase Letter 1
 
6.7%
Space Separator 1
 
6.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 4
36.4%
2 3
27.3%
5 2
18.2%
9 1
 
9.1%
1 1
 
9.1%
Lowercase Letter
ValueCountFrequency (%)
p 1
50.0%
t 1
50.0%
Uppercase Letter
ValueCountFrequency (%)
O 1
100.0%
Space Separator
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 12
80.0%
Latin 3
 
20.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 4
33.3%
2 3
25.0%
5 2
16.7%
9 1
 
8.3%
1
 
8.3%
1 1
 
8.3%
Latin
ValueCountFrequency (%)
O 1
33.3%
p 1
33.3%
t 1
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 15
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 4
26.7%
2 3
20.0%
5 2
13.3%
9 1
 
6.7%
O 1
 
6.7%
p 1
 
6.7%
t 1
 
6.7%
1
 
6.7%
1 1
 
6.7%

note
Text

MISSING 

Distinct11
Distinct (%)100.0%
Missing2588
Missing (%)99.6%
Memory size82.2 KiB
2024-09-19T19:18:50.029959image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Length

Max length105
Median length67
Mean length66.272727
Min length43

Characters and Unicode

Total characters729
Distinct characters44
Distinct categories9 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique11 ?
Unique (%)100.0%

Sample

1st rowalias_Name(pka) = American Board of Pedodontics
2nd rowalias_Name(pka) = American Board of Medical Specialties in Podiatry
3rd rowOtolaryngology/Plastic Surgery Within the Head and Neck
4th rowalias_Name(aka) = American Board of Otolaryngology-Head/Neck Surgery
5th rowalias_Name(pka) = American Board of Podiatric Surgery
ValueCountFrequency (%)
12
 
13.5%
of 9
 
10.1%
alias_name(pka 8
 
9.0%
board 7
 
7.9%
american 6
 
6.7%
podiatric 4
 
4.5%
surgery 3
 
3.4%
certification 3
 
3.4%
alias_name(aka 2
 
2.2%
and 2
 
2.2%
Other values (33) 33
37.1%
2024-09-19T19:18:50.632220image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
a 85
 
11.7%
78
 
10.7%
i 62
 
8.5%
e 49
 
6.7%
r 46
 
6.3%
o 43
 
5.9%
c 29
 
4.0%
t 27
 
3.7%
n 27
 
3.7%
s 24
 
3.3%
Other values (34) 259
35.5%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 529
72.6%
Space Separator 78
 
10.7%
Uppercase Letter 76
 
10.4%
Connector Punctuation 10
 
1.4%
Close Punctuation 10
 
1.4%
Open Punctuation 10
 
1.4%
Math Symbol 10
 
1.4%
Other Punctuation 5
 
0.7%
Dash Punctuation 1
 
0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a 85
16.1%
i 62
11.7%
e 49
9.3%
r 46
8.7%
o 43
 
8.1%
c 29
 
5.5%
t 27
 
5.1%
n 27
 
5.1%
s 24
 
4.5%
d 24
 
4.5%
Other values (11) 113
21.4%
Uppercase Letter
ValueCountFrequency (%)
P 16
21.1%
N 15
19.7%
B 9
11.8%
S 9
11.8%
A 8
10.5%
C 6
 
7.9%
O 3
 
3.9%
H 2
 
2.6%
W 2
 
2.6%
M 2
 
2.6%
Other values (4) 4
 
5.3%
Other Punctuation
ValueCountFrequency (%)
& 2
40.0%
/ 2
40.0%
, 1
20.0%
Space Separator
ValueCountFrequency (%)
78
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 10
100.0%
Close Punctuation
ValueCountFrequency (%)
) 10
100.0%
Open Punctuation
ValueCountFrequency (%)
( 10
100.0%
Math Symbol
ValueCountFrequency (%)
= 10
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 605
83.0%
Common 124
 
17.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
a 85
14.0%
i 62
 
10.2%
e 49
 
8.1%
r 46
 
7.6%
o 43
 
7.1%
c 29
 
4.8%
t 27
 
4.5%
n 27
 
4.5%
s 24
 
4.0%
d 24
 
4.0%
Other values (25) 189
31.2%
Common
ValueCountFrequency (%)
78
62.9%
_ 10
 
8.1%
) 10
 
8.1%
( 10
 
8.1%
= 10
 
8.1%
& 2
 
1.6%
/ 2
 
1.6%
- 1
 
0.8%
, 1
 
0.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 729
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
a 85
 
11.7%
78
 
10.7%
i 62
 
8.5%
e 49
 
6.7%
r 46
 
6.3%
o 43
 
5.9%
c 29
 
4.0%
t 27
 
3.7%
n 27
 
3.7%
s 24
 
3.3%
Other values (34) 259
35.5%

cme_reqhours
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size127.0 KiB
0
2599 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters2599
Distinct characters1
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 2599
100.0%

Length

2024-09-19T19:18:50.882895image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-09-19T19:18:51.061196image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
ValueCountFrequency (%)
0 2599
100.0%

Most occurring characters

ValueCountFrequency (%)
0 2599
100.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2599
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 2599
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 2599
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 2599
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2599
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 2599
100.0%

username
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing2599
Missing (%)100.0%
Memory size20.4 KiB

password
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing2599
Missing (%)100.0%
Memory size20.4 KiB

LegacyCD
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing2599
Missing (%)100.0%
Memory size20.4 KiB

obsolete
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size127.0 KiB
0
2598 
1
 
1

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters2599
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 2598
> 99.9%
1 1
 
< 0.1%

Length

2024-09-19T19:18:51.244523image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-09-19T19:18:51.426018image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
ValueCountFrequency (%)
0 2598
> 99.9%
1 1
 
< 0.1%

Most occurring characters

ValueCountFrequency (%)
0 2598
> 99.9%
1 1
 
< 0.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2599
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 2598
> 99.9%
1 1
 
< 0.1%

Most occurring scripts

ValueCountFrequency (%)
Common 2599
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 2598
> 99.9%
1 1
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2599
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 2598
> 99.9%
1 1
 
< 0.1%

lastvalidated
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing2599
Missing (%)100.0%
Memory size20.4 KiB

validatedby
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing2599
Missing (%)100.0%
Memory size20.4 KiB

CertificationBody
Categorical

HIGH CORRELATION  MISSING 

Distinct3
Distinct (%)5.4%
Missing2543
Missing (%)97.8%
Memory size142.1 KiB
ABMS
25 
AOA
20 
OTHER
11 

Length

Max length5
Median length4
Mean length3.8392857
Min length3

Characters and Unicode

Total characters215
Distinct characters9
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowABMS
2nd rowABMS
3rd rowOTHER
4th rowABMS
5th rowABMS

Common Values

ValueCountFrequency (%)
ABMS 25
 
1.0%
AOA 20
 
0.8%
OTHER 11
 
0.4%
(Missing) 2543
97.8%

Length

2024-09-19T19:18:51.652029image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-09-19T19:18:51.866462image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
ValueCountFrequency (%)
abms 25
44.6%
aoa 20
35.7%
other 11
19.6%

Most occurring characters

ValueCountFrequency (%)
A 65
30.2%
O 31
14.4%
B 25
 
11.6%
M 25
 
11.6%
S 25
 
11.6%
T 11
 
5.1%
H 11
 
5.1%
E 11
 
5.1%
R 11
 
5.1%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 215
100.0%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
A 65
30.2%
O 31
14.4%
B 25
 
11.6%
M 25
 
11.6%
S 25
 
11.6%
T 11
 
5.1%
H 11
 
5.1%
E 11
 
5.1%
R 11
 
5.1%

Most occurring scripts

ValueCountFrequency (%)
Latin 215
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
A 65
30.2%
O 31
14.4%
B 25
 
11.6%
M 25
 
11.6%
S 25
 
11.6%
T 11
 
5.1%
H 11
 
5.1%
E 11
 
5.1%
R 11
 
5.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 215
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
A 65
30.2%
O 31
14.4%
B 25
 
11.6%
M 25
 
11.6%
S 25
 
11.6%
T 11
 
5.1%
H 11
 
5.1%
E 11
 
5.1%
R 11
 
5.1%

isValidate
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size127.0 KiB
0
1512 
1
1087 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters2599
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 1512
58.2%
1 1087
41.8%

Length

2024-09-19T19:18:52.080597image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-09-19T19:18:52.265103image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
ValueCountFrequency (%)
0 1512
58.2%
1 1087
41.8%

Most occurring characters

ValueCountFrequency (%)
0 1512
58.2%
1 1087
41.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2599
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 1512
58.2%
1 1087
41.8%

Most occurring scripts

ValueCountFrequency (%)
Common 2599
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 1512
58.2%
1 1087
41.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2599
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 1512
58.2%
1 1087
41.8%

LicNumRequired
Categorical

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size127.0 KiB
1
2283 
0
316 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters2599
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1
2nd row1
3rd row1
4th row1
5th row1

Common Values

ValueCountFrequency (%)
1 2283
87.8%
0 316
 
12.2%

Length

2024-09-19T19:18:52.467235image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-09-19T19:18:52.652802image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
ValueCountFrequency (%)
1 2283
87.8%
0 316
 
12.2%

Most occurring characters

ValueCountFrequency (%)
1 2283
87.8%
0 316
 
12.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2599
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 2283
87.8%
0 316
 
12.2%

Most occurring scripts

ValueCountFrequency (%)
Common 2599
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 2283
87.8%
0 316
 
12.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2599
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 2283
87.8%
0 316
 
12.2%

isWFV
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size127.0 KiB
1
2599 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters2599
Distinct characters1
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1
2nd row1
3rd row1
4th row1
5th row1

Common Values

ValueCountFrequency (%)
1 2599
100.0%

Length

2024-09-19T19:18:52.855146image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-09-19T19:18:53.028467image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
ValueCountFrequency (%)
1 2599
100.0%

Most occurring characters

ValueCountFrequency (%)
1 2599
100.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2599
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 2599
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 2599
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 2599
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2599
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 2599
100.0%

isCredStrm
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size127.0 KiB
1
2599 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters2599
Distinct characters1
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1
2nd row1
3rd row1
4th row1
5th row1

Common Values

ValueCountFrequency (%)
1 2599
100.0%

Length

2024-09-19T19:18:53.212950image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-09-19T19:18:53.389151image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
ValueCountFrequency (%)
1 2599
100.0%

Most occurring characters

ValueCountFrequency (%)
1 2599
100.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2599
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 2599
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 2599
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 2599
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2599
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 2599
100.0%

Needs_Search_Info
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size127.0 KiB
0
2599 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters2599
Distinct characters1
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 2599
100.0%

Length

2024-09-19T19:18:53.577797image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-09-19T19:18:53.749885image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
ValueCountFrequency (%)
0 2599
100.0%

Most occurring characters

ValueCountFrequency (%)
0 2599
100.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2599
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 2599
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 2599
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 2599
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2599
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 2599
100.0%

Search_Info_Text
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing2599
Missing (%)100.0%
Memory size20.4 KiB

isManual
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size127.0 KiB
0
2481 
1
 
118

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters2599
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 2481
95.5%
1 118
 
4.5%

Length

2024-09-19T19:18:53.937984image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-09-19T19:18:54.117070image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
ValueCountFrequency (%)
0 2481
95.5%
1 118
 
4.5%

Most occurring characters

ValueCountFrequency (%)
0 2481
95.5%
1 118
 
4.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2599
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 2481
95.5%
1 118
 
4.5%

Most occurring scripts

ValueCountFrequency (%)
Common 2599
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 2481
95.5%
1 118
 
4.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2599
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 2481
95.5%
1 118
 
4.5%

Interactions

2024-09-19T19:18:24.045672image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-09-19T19:18:21.735169image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-09-19T19:18:23.331359image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-09-19T19:18:24.417475image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-09-19T19:18:22.255443image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-09-19T19:18:23.693729image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-09-19T19:18:24.591355image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-09-19T19:18:22.443782image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-09-19T19:18:23.874234image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Correlations

2024-09-19T19:18:54.271459image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
CertificationBodyLicNumRequiredautoemailautofaxinactiveisManualisValidatelatitudelinklongitudenationobsoletepayfeever_elec
CertificationBody1.0000.5000.3940.3940.1971.0000.9040.0000.4480.0000.4831.0000.7420.531
LicNumRequired0.5001.0000.1080.1040.0710.0760.2750.1540.4940.2730.1090.0000.1290.150
autoemail0.3940.1081.0000.9160.0000.0750.2580.1840.6540.1810.1580.0000.1400.675
autofax0.3940.1040.9161.0000.0000.0750.2500.1020.6320.2520.1570.0000.1650.673
inactive0.1970.0710.0000.0001.0000.0000.0400.1480.2290.1500.0000.0000.0000.099
isManual1.0000.0760.0750.0750.0001.0000.2510.0000.2180.0000.0000.0000.0000.136
isValidate0.9040.2750.2580.2500.0400.2511.0000.0000.4260.0000.2220.0000.1610.415
latitude0.0000.1540.1840.1020.1480.0000.0001.0000.054-0.4180.0001.0000.0760.103
link0.4480.4940.6540.6320.2290.2180.4260.0541.000-0.0270.2450.174-0.2950.692
longitude0.0000.2730.1810.2520.1500.0000.000-0.418-0.0271.0000.0001.000-0.0290.112
nation0.4830.1090.1580.1570.0000.0000.2220.0000.2450.0001.0000.0000.0000.235
obsolete1.0000.0000.0000.0000.0000.0000.0001.0000.1741.0000.0001.0000.0000.000
payfee0.7420.1290.1400.1650.0000.0000.1610.076-0.295-0.0290.0000.0001.0000.218
ver_elec0.5310.1500.6750.6730.0990.1360.4150.1030.6920.1120.2350.0000.2181.000

Missing values

2024-09-19T19:18:24.974125image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-09-19T19:18:25.974530image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.
2024-09-19T19:18:26.476599image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.

Sample

cdtxtaddraddr2citystatezipphonecontact1nationfaxcvo_typehomehtmlver_elecnewcdemailpayfeelinkautofaxautoemaillatitudelongitudeinactiveextensionnotecme_reqhoursusernamepasswordLegacyCDobsoletelastvalidatedvalidatedbyCertificationBodyisValidateLicNumRequiredisWFVisCredStrmNeeds_Search_InfoSearch_Info_TextisManual
09318VA New Jersey Health Care System-East Orange385 Tremont AveEast OrangeNJ07018-1023United StatesNaN00.0163404011NaNNaN0NaNNaN0NaNNaNNaN0NaNNaNNaN01110NaN0
1AAAASFAmerican Association for Accreditation of Ambulatory Surgery FacilitiesPo Box 9500American Association For Accreditation Of AmbulatoGurneeIL60031(847) 775-1970(847) 775-1985NaN00.0163577210NaNNaN0NaNNaN0NaNNaNNaN0NaNNaNNaN01110NaN0
2AAAHCAccreditation Association Ambulatory Health Care5250 Old Orchard RdSte 200SkokieIL60077-4461(847) 853-6060(847) 853-9028http://www.aaahc.org1info@aaahc.org0.0163577300NaNNaN0NaNNaN0NaNNaNNaN0NaNNaNNaN01110NaN0
3AAAPAmerican Academy of Addiction Psychiatry400 Massasoit AveSte 307East ProvidenceRI02914-2012(401) 524-3076United StatesNaN00.0163804700NaNNaN0NaNNaN0NaNNaNNaN0NaNNaNNaN01110NaN0
4AABIMAmerican Audiology Board of Intraoperative Monitoring563 Carter CtSte BKimberlyWI54136(920) 560-5631United StatesNaN0info@aabiom.com0.0163778211NaNNaN0NaNNaN0NaNNaNNaN0NaNNaNNaN01110NaN0
5AABIPThe American Association of Bronchology & Interventional Pulmonology445 Minnesota StSte 1500Saint PaulMN55101-2269(651) 256-9506www.aabronchology.org0info@aabronchology.org0.0163746411NaNNaN0NaNNaN0NaNNaNNaN0NaNNaNNaN01110NaN0
6AABMAAmerican Academy/Board of Medical Acupuncture2512 Artesia Blvd Ste 200Redondo BeachCA90278-3279(310) 379-8261NaN0info@medicalacupuncture.org0.0163577401NaNNaN0NaNNaN0NaNNaNNaN0NaNNaNNaN01110NaN0
7AACADDAmerican Academy of Health Care Providers in the Addictive Disorders314 W Superior StSte 508DuluthMN55802(218) 727-3940United States(218) 722-0346https://americanacademy.org/0info@americanacademy.org0.0163825800NaNNaN0NaNNaN0NaNNaNNaN0NaNNaNNaN01110NaN0
8AACNAmerican Association of Critical Care Nurse Certification101 ColumbiaAliso ViejoCAhttps://www.aacn.org/dm/CustomerProfile/Login.aspx?mid=2869&0certification@aacn.org0.0163732411NaNNaN0NaNNaN0NaNNaNNaN0NaNNaNNaN11110NaN0
9AACPAmerican Association of Community Psychiatrists94 Auburn StSte 110PortlandME04103-2141(207) 878-6170(207) 878-6172NaN00.0163767911NaNNaN0NaNNaN0NaNNaNNaN0NaNNaNNaN01110NaN0
cdtxtaddraddr2citystatezipphonecontact1nationfaxcvo_typehomehtmlver_elecnewcdemailpayfeelinkautofaxautoemaillatitudelongitudeinactiveextensionnotecme_reqhoursusernamepasswordLegacyCDobsoletelastvalidatedvalidatedbyCertificationBodyisValidateLicNumRequiredisWFVisCredStrmNeeds_Search_InfoSearch_Info_TextisManual
2589ZZNEDENorth East Regional Board of Dental Examiners8484 Georgia Ave Ste 900Silver SpringMD20910-5604(301) 563-3300NaN00.8816370540038993810.0-77026699.01NaNNaN0NaNNaNNaN0NaNNaNNaN01110NaN0
2590ZZNOCANational Organization for Competency Assurance2025 M St NwSte 800WashingtonDC20036-2422(202) 367-1165NaN00.881637055000.00.01NaNNaN0NaNNaNNaN0NaNNaNNaN01110NaN0
2591ZZNOPANational Board for Certification of Orthopaedic Physician Assistant8365 Keystone XingSte 107IndianapolisIN46240(800) 280-2390United Stateshttps://nbcopa.org/verification/10.881637056000.00.01NaNNaN0NaNNaNNaN0NaNNaNNaN01110NaN0
2592ZZNTMBNational Certification Board for Therapeutic Massage/Bodywork1901 S Meyers Rd Ste 240Oakbrook TerraceIL60181-5206(800) 296-0664NaN00.881637057000.00.01NaNNaN0NaNNaNNaN0NaNNaNNaN01110NaN0
2593ZZONCBOrthopaedic Nurses Certification BoardPO Box 87ColumbiaSC29202(888) 561-6622NaN00.8816370580034000900.081035300.01NaNNaN0NaNNaNNaN0NaNNaNNaN01110NaN0
2594ZZOPAAmerican Society of Orthopaedic Physicians Assistants8365 Keystone Xing Ste 107IndianapolisIN46240-2685(800) 280-2390NaN00.881637059000.00.01NaNNaN0NaNNaNNaN0NaNNaNNaN01110NaN0
2595ZZOPSOphthalmic Photographers Society1887 W Ranch RdNixaMO65714-8262(800) 403-1677NaN00.881637060000.00.01NaNNaN0NaNNaNNaN0NaNNaNNaN01110NaN0
2596ZZPNSAmerican Board of Pediatric Neurological Surgeryno address availableNaN00.881637061000.00.01NaNNaN0NaNNaNNaN0NaNNaNNaN10110NaN0
2597ZZRCPSRoyal College of Physicians & Surgeons Canada774 Echo DrOttawaONK1S 5N8(613) 730-8177Canadahttps://rclogin.royalcollege.ca/webcenter/portal/rcdirectory_en10.881637062000.00.01NaNNaN0NaNNaNNaN0NaNNaNNaN00110NaN0
2598ZZSCAISociety for Cardiovascular Angiography/Intervention2400 N St NwWashingtonDC20037(202) 375-6195NaN00.00163706301NaNNaN1NaNNaN0NaNNaNNaN0NaNNaNNaN01110NaN0